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The dataset aims to compile images of buildings with structural damage for analysis. The images can be classified by the severity of damage to building facades after seismic events using deep learning techniques, particularly pre-trained convolutional neural networks and transfer learning. The analysis can precisely identify structural damage levels, aiding in effective evaluation and response strategies.
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Microsoft contains a productive tool known as MS Office but the inclusion of VBA Macros inside the MS Office for automation purposes makes it a way for attackers to perform malicious activities. To get an up-to-date dataset, the research regarding VBA macros is still working to find efficient ways to detect it. To perform analysis, the dataset is required which is publically harder to find. To overcome this issue, a dataset is created from VirusTotal, VirusShare, Zenodo, Malware Bazaar, Github and InQuest Labs.
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The impact of high curvature bending on thin film transistor(TFT) performance is of interest for flexible electronics. Bending influences TFT performance in two ways. First due to mechanical stress and second due to the pure geometric effect of converting a planar architecture to a cylindrical one. Experiments to simultaneously create and yet distinguish these two effects are difficult. Analytical models are required to identify the individual impact of stress and geometry. The goal of this work is to identify the purely geometrical impact on TFT characteristics.
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The Annual Retail Trade Survey (ARTS) produces national estimates of total annual sales, e-commerce sales, end-of-year inventories, inventory-to-sales ratios, purchases, total operating expenses, inventories held outside the United States, gross margins, and end-of-year accounts receivable for retail businesses and annual sales and e-commerce sales for accommodation and food service firms located in the U.S.
License: U.S. Government Work
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